• Journal of the Korea Society of Computer and Information
• /
• v.17 no.1
• /
• pp.71-80
• /
• 2012

This paper proposes vehicle detection and tracking algorithm using a CCD camera. The proposed algorithm uses Haar-like wavelet edge detector to detect features of vehicle and estimates vehicle's location using calibration information of an image. After that, extract accumulated vehicle information in continuous k images to improve reliability. Finally, obtained vehicle region becomes a template image to find same object in the next continuous image using SURF(Speeded Up Robust Features). The template image is updated in the every frame. In order to reduce SURF processing time, ROI(Region of Interesting) region is limited on expended area of detected vehicle location in the previous frame image. This algorithm repeats detection and tracking progress until no corresponding points are found. The experimental result shows efficiency of proposed algorithm using images obtained on the road.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.3
• /
• pp.31-38
• /
• 2003

In the present work, a nonlinear inverse perturbation method which has been used in the structural optimization, is adopted so as to identify the structural damages. Unlike the structural optimization, a larger number of constrained equations than the number of unknown parameters are often required detect structural damage. Therefore, nonlinear least squares method is utilized to solve the problem. Because only a limited number of sensors are available I real situation of damage detection, the determination of sensor location becomes one of the most important issues. Hence, this work concentrates on the issue of sensor placement in the framework of nonlinear inverse perturbation method, and the performances of various methodologies concerning to sensor placement are compared with each other. The comparisons show tat the successive elimination method gets good performance for sensor placement. From the several numerical studies, it is confirmed that the inverse perturbation method, combined with the successive elimination method, is very promising in structural damage detection.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.11
• /
• pp.637-644
• /
• 2014

This paper investigates the detection performance of fault location using STDR(sequence time domain reflectometry) and SSTDR(spread spectrum time domain reflectometry) with various length and types of sequences, and then, proposes an improved detection technique by eliminating the injected signal in SSTDR. The detection error rates are compared and analyzed in power line channel model with various fault locations, fault types, and spreading sequences such as m-sequence, binary Barker sequence, and 4-phase Frank sequence. It is shown that the proposed technique is able to improve the detection performance obviously when the reflected signal is weak or the fault location is extremely close.

• Smart Structures and Systems
• /
• v.23 no.2
• /
• pp.107-122
• /
• 2019

As one of the most important parameters in structural health monitoring, structural frequency has many advantages, such as convenient to be measured, high precision, and insensitive to noise. In addition, frequency-change-ratio based method had been validated to have the ability to identify the damage occurrence and location. However, building a precise enough finite elemental model (FEM) for the test structure is still a huge challenge for this frequency-change-ratio based damage detection technique. In order to overcome this disadvantage and extend the application for frequencies in structural health monitoring area, a novel method was developed in this paper by combining the cross-model cross-mode (CMCM) model updating algorithm with the frequency-change-ratio based method. At first, assuming the physical parameters, including the element mass and stiffness, of the test structure had been known with a certain value, then an initial to-be-updated model with these assumed parameters was constructed according to the typical mass and stiffness distribution characteristic of shear buildings. After that, this to-be-updated model was updated using CMCM algorithm by combining with the measured frequencies of the actual structure when no damage was introduced. Thus, this updated model was regarded as a representation of the FEM model of actual structure, because their modal information were almost the same. Finally, based on this updated model, the frequency-change-ratio based method can be further proceed to realize the damage detection and localization. In order to verify the effectiveness of the developed method, a four-level shear building was numerically simulated and two actual shear structures, including a three-level shear model and an eight-story frame, were experimentally test in laboratory, and all the test results demonstrate that the developed method can identify the structural damage occurrence and location effectively, even only very limited modal frequencies of the test structure were provided.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.6
• /
• pp.61-73
• /
• 2020

Real-time location-sensing technology using location information collected from IoT devices is being applied for safety management purposes in many industries, such as ports. On the other hand, positional error is always present owing to the characteristics of GPS. Therefore, accident-risk detection algorithms must consider positional error. This paper proposes an methodology of calibration for falling object accident-risk-zone approach detection algorithm considering GPS errors. A probability density function was estimated, with positional error data collected from IoT devices as a probability variable. As a result of the verification, the algorithm showed a detection accuracy of 93% and 77%. Overall, the analysis results derived according to the GPS error level will be an important criterion for upgrading algorithms and real-time risk managements in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.10a
• /
• pp.50-53
• /
• 2022

In order to detect an object in yolv5, a process of annotating location information on an existing image is required when learning an image. The most representative method is to draw a bounding box on an image to store location information as meta information. However, if the boundary of the object is ambiguous, it will be difficult to make a bounding box. A representative example would be to classify parts that are not fire and parts that are fire. Therefore, in this paper, images of 100 samples judged to have caught fire were learned by varying the number of boxes. The results showed better fire detection performance in the model where the bounding box was trained by annotating it with three boxes by segmenting it slightly more than annotating it with one box by holding the edge as large as possible during annotating it with one box.

• Structural Engineering and Mechanics
• /
• v.30 no.6
• /
• pp.699-712
• /
• 2008

The effectiveness of wavelet transform in detecting delamination damages in multilayered composite beams and plates is studied here. The damaged composite beams and plates are modeled in finite element software ABAQUS and the first few mode shapes are obtained. The mode shapes of the damaged structures are then wavelet transformed. It is observed that the distribution of wavelet coefficients can identify the damage location of beams and plates by showing higher values of wavelet coefficients at the position of damage. The effectiveness of the method is studied for different boundary conditions, damage location and size for single as well as multiple delaminations in composite beams and plates. It is observed that both discrete wavelet transform (DWT) and continuous wavelet transform (CWT) can detect the presence and location of the damaged region from the mode shapes of the structures. DWT may be used to approximately evaluate the size of the delamination area, whereas, CWT is efficient to detect smaller delamination areas in composites.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.18 no.3
• /
• pp.217-224
• /
• 2013

This paper presents a diagnostic method for a sparse matrix converter that detects faults in any single switch or a pair of switches. The sparse matrix converter is functionally equivalent to the standard matrix converter but has a reduced number of switches. The proposed diagnostic method is based in the measurement of input and output currents. The currents have respective characteristic according to the location of faulty switches. This method not only detects the switches of open-circuit fault but identifies the location of the faulty switching devices without complicated calculations. The simulation and experimental results verify that, based on the proposed method, the fault of sparse matrix converter can be easily and fast detected.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1996.10a
• /
• pp.138-146
• /
• 1996

The presence of a damage, such as a crack, in a structure increases the flexibility and damping in the structure. Most of methods to detect damage or damage location uses stiffness matrix of the structural system. The modification of stiffness matrix, however, has complicated procedures to identify structural. system in the basis of finite element model and has too many degree of freedom to calculate. Identification of changes of flexibility of structure can offer damage information immediately and simple procedure can employ real time continuous monitoring system. To identify changes of the flexibility, vibration mode shapes and natural frequencies are usually used. In this paper, a procedure for damage location in continuous girder bridges using vibration data is described. The effectiveness and sensitivity of the presented method to measurement errors in mode shapes and natural frequencies are investigated using analytical results from finite element models. It is shown that the errors in the first mode shape and first natural frequency demonstrate much larger influence than those in the higher mode shapes and modal frequencies.

• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.240-243
• /
• 1995

In excavating tunnels, shield tunneling machines having many cutters on their cutter planes are used. Not many observation data being available in the detection system, optimal observation policy is very important. From this viewpoint, we previously considered the optimal location of acoustic sensors on the cutter plane and also the optimal observation policy for the case where three receiving transducers were used, and showed that the optimal sensor location was given as arbitrary equally-spaced points on the cutter plane circle, and that the optimal rotating angles were also found to be arbitrary. In application, however, it is often difficult to locate sensors at arbitrary positions or to use three sensors from the viewpoints of machine structure and cost. This paper considers the optimal observation policy for detecting anomlous plane objects for the case where two receiving transducers are used and the case where three receiving transducers are located only on a diameter of the cutter plane.